Geof Bowker's Papers


This is an occasional collection of papers (viz updated occasionally).


How things actor-network

Lest we remember

Of lungs and lungers

Multiple bodies of the record

Things Come Together - Information Convergence

Some recent literature of cyberspace

Building the next generation Biological Information Infrastructure

Sorting Things Out: Classification and Its Consequences

Biodiversity datadiversity

Mapping Biodiversity

Theoretical Issues in the Design of Collaboratories

On new infrastructures for distributed knowledge

Pure, Real and Rational Numbers: The American Imaginary of Countability

The Knowledge Economy

Instrumentalizing the Truth of Practice

Keeping Knowledge Local

Time, Money and Biodiversity

An International Framework to Promote Access to Data

The Past and the Internet

Promoting Access to Data

A Learning Trajectory for Ontology Building

Information Ecology: Open System Environment for Data, Memories and Knowing

That Elusive Object of Desire: a science studies history of science studies

Metadata , trajectoires et « énaction » (avec Florence Millerand)

Metadata: Trajectories and Enactment in the Life of an Ontology (with Florence Millerand)

Future Directions in ICT Research

Living in the Human World

Fog of Data (webcast)

Information Infrastructures for Distributed Collective Practices (with Bill Turner, Les Gasser and Manuel Zacklad) (note - requires institutional access to CSCW - email me if this is a problem)

A Plea for Pleats

Infrastructure and its Orphans (video of talk with Susan Leigh Star)

Toward Cyberinfrstructure Studies (NSF Report)

Interview with Geof Bowker and Susan Leigh Star (Italian)

Extending African Knowledge Infrastructures (with Steve Jackson, Paul Edwards, Archer Bacheller, Steve Cisler and Leigh Star)

All knowledge is local (talk)

Feminist science and technology studies: A patchwork of moving subjectivities (interview with Geoffrey Bowker, Sandra Harding, Anne Marie Mol, Susan Leigh Star and Banu Subramaniam)

Between meaning and machine: Learning to represent
the knowledge of communities

All Knowledge Is Local

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